Examples that match the current platform

These guides are now aligned with the current API To MCP flow: the visual UI Wizard, the manager MCP for AI agents, OAuth 2.0 support, workflow tools, REST, and GraphQL.

How to read these examples

  • Each guide starts with the best auth model for that API, not just a list of endpoints.
  • Each guide covers both creation paths: the visual builder and the manager MCP.
  • Examples focus on production choices: public MCP, internal MCP, or per-user OAuth.
  • Workflow tools are included only when they add value beyond a single endpoint call.

Two production-ready creation flows

Visual UI Wizard

Open the builder, choose REST or GraphQL, select the correct auth type, define tools, test them, and deploy.

AI Agent via Manager MCP

Connect the official manager MCP, point your AI agent at the API documentation, and let it create, update, test, and deploy the MCP server from chat.

https://mcp.apitomcp.app/

Example library

Choosing the right auth model

Open or API-key public data

Best for public APIs, weather, datasets, and low-risk discovery tools that end users can connect to directly.

Stored business credentials

Best for internal tools where one owner-managed API credential should power the live MCP server.

OAuth Authorization Code

Best when every employee or end user should connect their own Google, Meta, CRM, or SaaS account.

Workflow tools

Best when the agent needs one clean tool that chains multiple API steps and returns a simpler result.

Start from the UI or from an agent

If you want the fastest path, use the builder. If you want AI to assemble the server for you, connect the manager MCP and use a prompt like this:

Read the API documentation for this platform and create an MCP server with useful read tools first.
Choose the correct authentication model, add clean tool descriptions, shape the outputs for AI clients,
test the server, then return the deployed MCP URL and any setup steps I still need to complete.